Dataset Information

DNA Methylation in Ovarian Cancer Susceptibility.

ABSTRACT: Epigenetic alterations are somatically acquired over the lifetime and during neoplastic transformation but may also be inherited as widespread 'constitutional' alterations in normal tissues that can cause cancer predisposition. Epithelial ovarian cancer (EOC) has an established genetic susceptibility and mounting epidemiological evidence demonstrates that DNA methylation (DNAm) intermediates as well as independently contributes to risk. Targeted studies of known EOC susceptibility genes (CSGs) indicate rare, constitutional BRCA1 promoter methylation increases familial and sporadic EOC risk. Blood-based epigenome-wide association studies (EWAS) for EOC have detected a total of 2846 differentially methylated probes (DMPs) with 71 genes replicated across studies despite significant heterogeneity. While EWAS detect both symptomatic and etiologic DMPs, adjustments and analytic techniques may enrich risk associations, as evidenced by the detection of dysregulated methylation of BNC2-a known CSG identified by genome-wide associations studies (GWAS). Integrative genetic-epigenetic approaches have mapped methylation quantitative trait loci (meQTL) to EOC risk, revealing DNAm variations that are associated with nine GWAS loci and, further, one novel risk locus. Increasing efforts to mapping epigenome variation across populations and cell types will be key to decoding both the genomic and epigenomic causal pathways to EOC.

SUBMITTER: Reid BM

PROVIDER: S-EPMC7795210 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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DNA Methylation in Ovarian Cancer Susceptibility.

Reid Brett M BM Fridley Brooke L BL

Cancers 20201231 1

Epigenetic alterations are somatically acquired over the lifetime and during neoplastic transformation but may also be inherited as widespread 'constitutional' alterations in normal tissues that can cause cancer predisposition. Epithelial ovarian cancer (EOC) has an established genetic susceptibility and mounting epidemiological evidence demonstrates that DNA methylation (DNAm) intermediates as well as independently contributes to risk. Targeted studies of known EOC susceptibility genes (CSGs) i ...[more]

PMID: 33396385

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Project description:BACKGROUND:Ovarian cancer (OC) is the most lethal gynecological cancer, worldwide, largely due to its vague and nonspecific early stage symptoms, resulting in most tumors being found at advanced stages. Moreover, due to its relative rarity, there are currently no satisfactory methods for OC screening, which remains a controversial and cost-prohibitive issue. Here, we demonstrate that Papanicolaou test (Pap test) cervical scrapings, instead of blood, can reveal genetic/epigenetic information for OC detection, using specific and sensitive DNA methylation biomarkers. RESULTS:We analyzed the methylomes of tissues (50 OC tissues versus 6 normal ovarian epithelia) and cervical scrapings (5 OC patients versus 10 normal controls), and integrated public methylomic datasets, including 79 OC tissues and 6 normal tubal epithelia. Differentially methylated genes were further classified by unsupervised hierarchical clustering, and each candidate biomarker gene was verified in both OC tissues and cervical scrapings by either quantitative methylation-specific polymerase chain reaction (qMSP) or bisulfite pyrosequencing. A risk-score by logistic regression was generated for clinical application. One hundred fifty-one genes were classified into four clusters, and nine candidate hypermethylated genes from these four clusters were selected. Among these, four genes fulfilled our selection criteria and were validated in training and testing set, respectively. The OC detection accuracy was demonstrated by area under the receiver operating characteristic curves (AUCs) in 0.80-0.83 of AMPD3, 0.79-0.85 of AOX1, 0.78-0.88 of NRN1, and 0.82-0.85 of TBX15. From this, we found OC-risk score, equation generated by logistic regression in training set and validated an OC-associated panel comprising AMPD3, NRN1, and TBX15, reaching a sensitivity of 81%, specificity of 84%, and OC detection accuracy of 0.91 (95% CI, 0.82-1) in testing set. CONCLUSIONS:Ovarian cancer detection from cervical scrapings is feasible, using particularly promising epigenetic biomarkers such as AMPD3/NRN1/TBX15. Further validation is warranted.

Project description:BACKGROUND:Ovarian cancer is an epithelial malignancy that intrigues people for its poor outcome and lack of efficient treatment, while methylation is an important mechanism that have been recognized in many malignancies. In this study, we attempt to assess abnormally methylated gene markers and pathways in ovarian cancer by integrating three microarray datasets. METHODS:Three datasets including expression (GSE26712 and GSE66957) and methylation (GSE81224) datasets were accessed. GEO2R platform was used to detect abnormally methylated-differentially expressed genes. Protein-protein interaction (PPI) networks were built and analysed for hypermethylated and hypermethylated differentially expressed genes using Cytoscape software and Mcode app. GEPIA and cBioPortal platforms were used to validate the expression of the hub genes and the correlation between their mRNA expressions and methylation levels. Kaplan Meier-plotter platform were used to assess the prognostic significance of the hub genes. RESULTS:Six hundred eighty-one hypomethylated-upregulated genes were detected and involved in Rap1 signaling pathway, biosynthesis of amino acids, endocrine resistance, apoptosis, pathways in cancer. The hub genes were TNF, UBC, SRC, ESR1, CDK1, PECAM1, CXCR4, MUC1, IKBKG. Additionally, 337 hypermethylated-downregulated genes were detected and involved in pathways in cancer, focal adhesion, sphingolipid signaling pathway, EGFR tyrosine kinase inhibitor resistance, cellular senescence. The hub genes were BDNF, CDC42, CD44, PPP2R5C, PTEN, UBB, BMP2, FOXO1, KLHL2. TNF, ESR1, MUC1, CD44, PPP2R5C, PTEN, UBB and FOXO1 showed significant negative correlation between their mRNA expressions and methylation levels. TNF, ESR1 and FOXO1 showed prognostic significance. CONCLUSIONS:Two novel gene networks were found for ovarian cancer. TNF, ESR1, MUC1 and FOXO1 are our candidate genes that might take part in ovarian cancer progression in an epigenetic approach, TNF, ESR1 and FOXO1 may serve as potential markers for ovarian cancer prognosis evaluation.

Project description:BACKGROUND: The GBGT1 gene encodes the globoside alpha-1,3-N-acetylgalactosaminyltransferase 1. This enzyme catalyzes the last step in the multi-step biosynthesis of the Forssman (Fs) antigen, a pentaglycosyl ceramide of the globo series glycosphingolipids. While differential GBGT1 mRNA expression has been observed in a variety of human tissues being highest in placenta and ovary, the expression of GBGT1 and the genes encoding the glycosyltransferases and glycosidases involved in the biosynthesis of Fs as well as the possible involvement of DNA methylation in transcriptional regulation of GBGT1 expression have not yet been investigated. RESULTS: RT-qPCR profiling showed high GBGT1 expression in normal ovary surface epithelial (HOSE) cell lines and low GBGT1 expression in all (e.g. A2780, SKOV3) except one (OVCAR3) investigated ovarian cancer cell lines, a finding that was confirmed by Western blot analysis. Hierarchical cluster analysis showed that GBGT1 was even the most variably expressed gene of Fs biosynthesis-relevant glycogenes and among the investigated cell lines, whereas NAGA which encodes the alpha-N-acetylgalactosaminidase hydrolyzing Fs was not differentially expressed. Bisulfite- and COBRA-analysis of the CpG island methylation status in the GBGT1 promoter region demonstrated high or intermediate levels of GBGT1 DNA methylation in all ovarian cancer cell lines (except for OVCAR3) but marginal levels of DNA methylation in the two HOSE cell lines. The extent of DNA methylation inversely correlated with GBGT1 mRNA and protein expression. Bioinformatic analysis of GBGT1 in The Cancer Genome Atlas ovarian cancer dataset demonstrated that this inverse correlation was also found in primary ovarian cancer tissue samples confirming our cell line-based findings. Restoration of GBGT1 mRNA and protein expression in low GBGT1-expressing A2780 cells was achieved by 5-aza-2'-deoxycytidine treatment and these treated cells exhibited increased helix pomatia agglutinin-staining, reflecting the elevated presence of Fs disaccharide on these cells. CONCLUSIONS: GBGT1 expression is epigenetically silenced through promoter hypermethylation in ovarian cancer. Our findings not only suggest an involvement of DNA methylation in the synthesis of Fs antigen but may also explain earlier studies showing differential GBGT1 expression in various human tissue samples and disease stages.

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DNA Methylation in Ovarian Cancer Susceptibility.

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DNA Methylation in Ovarian Cancer Susceptibility.

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